The Problem Canton Solves

Blockchain technology promises shared truth between parties who don’t fully trust each other. But traditional blockchains achieve this trust through total public visibility—everyone sees everything. For many real-world applications, this is a dealbreaker.

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The Public Visibility Problem

Consider what happens on Ethereum when Alice trades with Bob:

1. Alice submits a transaction
2. The transaction enters the mempool (visible to everyone)
3. Miners/validators include it in a block
4. Every node in the network stores the transaction
5. Anyone can query the transaction details forever

This means:

• Charlie can see that Alice traded with Bob
• Charlie can see the price, the asset, and the amounts
• Charlie can analyze Alice’s trading patterns over time
• If Charlie is a competitor, he now has valuable intelligence

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Why Privacy Matters

The public transparency problem isn’t theoretical. It blocks real adoption:

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Front-Running Risk

When transactions are visible before and during execution, observers can exploit that information. In traditional finance, this is illegal. On transparent blockchains, it’s structural.

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Competitive Intelligence

Every transaction reveals information:

• Trading strategies: Pattern analysis exposes your approach
• Business relationships: Who you transact with reveals partners
• Position sizes: Competitors learn your exposure
• Pricing information: Counterparties see your other deals

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Regulatory Barriers

Many industries have legal requirements around data:

• Financial regulations: Client data must be protected
• Data sovereignty: Information may not leave certain jurisdictions
• Confidentiality obligations: Contractual privacy requirements

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Business Reality

No enterprise will put sensitive business logic and transactions on a system where competitors can read it. Period.

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Imperfect Mitigating Solutions

The industry has tried several approaches to add privacy to transparent blockchains:

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Private Channels

Systems like Hyperledger Fabric create separate channels for subsets of participants. Problems:

• Fragmentation: No shared state across channels
• Complexity: Managing channel membership
• Limited interoperability: Cross-channel transactions are difficult

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Zero-Knowledge Proofs

ZK-rollups and ZK-based systems prove transaction validity without revealing content. Problems:

• Computational overhead: Proof generation is expensive
• Complexity: ZK circuits are difficult to develop and audit
• Limited expressiveness: Not all business logic fits ZK constraints
• Trusted setup requirements: Some systems require trust assumptions

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Layer 2 Solutions

Moving transactions off the main chain and settling on-chain periodically. Problems:

• Data availability: L2 operators typically see all transactions
• Trust assumptions: Users must trust L2 operators
• Settlement delays: Finality requires waiting for L1 confirmation
• Bridge risks: Moving assets between layers introduces attack surface

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Encryption at Rest

Encrypting data stored on-chain. Problems:

• Key management: Who holds decryption keys?
• Metadata exposure: Transaction patterns still visible
• Future vulnerability: Encrypted data today may be decrypted tomorrow
• Computation limits: Can’t compute on encrypted data easily

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The Fundamental Tension

These approaches all treat privacy as something to add on top of a transparent system. They’re fighting against the architecture, not working with it. The fundamental tension is: Traditional blockchains force you to choose: integrity or privacy.

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Canton’s Insight

Canton resolves this tension by changing what “consensus” means:

• Validators don’t need to see transactions they’re not part of
• Consensus can be achieved by the parties involved in a transaction
• A coordinator can order transactions without seeing their content

This isn’t a workaround—it’s a different architectural foundation. Privacy is built into how transactions work, not layered on top.

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Next Steps